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WiSee uses modified Wi-Fi router to recognise gestures through walls

Computer scientists at the University of Washington have developed a way to use a modified Wi-Fi router to detect specific gestures -- even through walls -- without the need for additional sensors or cameras.

The technology, called WiSee, allows users to control electronic devices from any room in the home with simple gestures. According to a study led by assistant professor Shyam Gollokota, WiSee can identify and classify a set of nine gestures with an average accuracy of 94 percent.

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Conventional gesture recognition technologies such as Kinect tend to involve cameras and depth sensors. However, these devices can only recognise gestures in the room where the sensor is.

Alternative techniques have tried to harness on-body sensors.

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WiSee's "whole-home gesture recognition system" doesn't need any user instrumentation or array of cameras. Instead it relies on analysing the Wi-Fi signals within an environment. Wi-Fi signals can travel through walls, meaning that only a few sources -- such as the Wi-Fi access point connected to the router and a couple of mobile devices -- are needed to be able to position people (and their gestures) within a building.

WiSee looks at subtle Doppler shifts and multi-path distortions that occur in these Wi-Fi signals when humans move within the environment. With the Doppler shift part, WiSee looks for the frequency change of a wave as its source moves relative to the observer -- the same effect we hear with the changing pitch of a siren as an emergency vehicle passes us. In the context of WiSee, the reflections of the Wi-Fi signal as they bounce off the human body are seen as the source. This means that when a human performs a gesture, it creates a specific pattern of Doppler shifts that are picked up by the wireless receiver. So moving one's hand away from the receiver would be a negative Doppler shift and moving it towards the receiver would be a negative one. The team had to map a number of different gestures -- including a bowling movement, a kick, a punch and circling the hand -- to the Doppler shifts they created.

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WiSee

The problem is that regular human hand gestures create very small Doppler shifts -- of just several hertz -- that can be difficult to detect by typical household Wi-Fi equipment.

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Researchers first had to adapt a Wi-Fi router to become a smart receiver device that could listen to all of the wireless transmissions coming from devices in the home. They then built an algorithm to transform the broadband signal usually received by Wi-Fi receivers into a narrowband signal, which allowed it to detect the very slight changes in frequency which result from human gestures.

WiSee's algorithm converts the broadband signal into narrowband so that it can detect subtle signal shifts caused by human gestures

WiSee

A further challenge was dealing with multiple people in the same space at the same time. WiSee gets round this by looking for gestural triggers, where a person can take control of the system by performing a specific gesture pattern. WiSee was tested with five users in both an office environment and a two-bedroom apartment. Gestures were performed in line-of-sight, non-line-of-sight and through walls. When there were more people in the space, the accuracy was lower -- less than 60 percent when there were four interfering people.

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The authors concluded: "Our results in a two bedroom apartment show that WiSee can extract a rich set of gesture information from wireless signals and enable whole-home gesture recognition using only two wireless sources placed in the living room.

Shyam Gollokota's collaborators Shwetak Patel and Sidhant Gupta have worked with Microsoft Research on a couple of similar technologies -- SoundWave and Humantenna. The former uses sound and the latter uses radiation from electrical wires to sense whole-body gestures. However, WiSee is the only system which works through walls.